CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting

Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome. To drive innovation in this area, we setup a community-wide challenge using the largest available dataset of its kind to assess nuclear segmentation and cellular composition. Our challenge, named CoNIC, stimulated the development of reproducible algorithms for cellular recognition with real-time result inspection on public leaderboards. We conducted an extensive post-challenge analysis based on the top-performing models using 1,658 whole-slide images of colon tissue. With around 700 million detected nuclei per model, associated features were used for dysplasia grading and survival analysis, where we demonstrated that the challenge's improvement over the previous state-of-the-art led to significant boosts in downstream performance. Our findings also suggest that eosinophils and neutrophils play an important role in the tumour microevironment. We release challenge models and WSI-level results to foster the development of further methods for biomarker discovery

Epitope-preserving magnified analysis of proteome (eMAP)

Synthetic tissue-hydrogel methods have enabled superresolution investigation of biological systems using diffraction-limited microscopy. However, chemical modification by fixatives can cause loss of antigenicity, limiting molecular interrogation of the tissue gel. Here, we present epitope-preserving magnified analysis of proteome (eMAP) that uses purely physical tissue-gel hybridization to minimize the loss of antigenicity while allowing permanent anchoring of biomolecules. We achieved success rates of 96% and 94% with synaptic antibodies for mouse and marmoset brains, respectively. Maximal preservation of antigenicity allows imaging of nanoscopic architectures in 1000-fold expanded tissues without additional signal amplification. eMAP-processed tissue gel can endure repeated staining and destaining without epitope loss or structural damage, enabling highly multiplexed proteomic analysis. We demonstrated the utility of eMAP as a nanoscopic proteomic interrogation tool by investigating molecular heterogeneity in inhibitory synapses in the mouse brain neocortex and characterizing the spatial distributions of synaptic proteins within synapses in mouse and marmoset brains

Pathobiological Pseudohypoxia as a Putative Mechanism Underlying Myelodysplastic Syndromes.

Myelodysplastic syndromes (MDS) are heterogeneous hematopoietic disorders that are incurable with conventional therapy. Their incidence is increasing with global population aging. Although many genetic, epigenetic, splicing, and metabolic aberrations have been identified in patients with MDS, their clinical features are quite similar. Here, we show that hypoxia-independent activation of hypoxia-inducible factor 1α (HIF1A) signaling is both necessary and sufficient to induce dysplastic and cytopenic MDS phenotypes. The HIF1A transcriptional signature is generally activated in MDS patient bone marrow stem/progenitors. Major MDS-associated mutations (Dnmt3a, Tet2, Asxl1, Runx1, and Mll1) activate the HIF1A signature. Although inducible activation of HIF1A signaling in hematopoietic cells is sufficient to induce MDS phenotypes, both genetic and chemical inhibition of HIF1A signaling rescues MDS phenotypes in a mouse model of MDS. These findings reveal HIF1A as a central pathobiologic mediator of MDS and as an effective therapeutic target for a broad spectrum of patients with MDS.Significance: We showed that dysregulation of HIF1A signaling could generate the clinically relevant diversity of MDS phenotypes by functioning as a signaling funnel for MDS driver mutations. This could resolve the disconnection between genotypes and phenotypes and provide a new clue as to how a variety of driver mutations cause common MDS phenotypes. Cancer Discov; 8(11); 1438-57. ©2018 AACR. See related commentary by Chen and Steidl, p. 1355 This article is highlighted in the In This Issue feature, p. 1333